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Postdoctoral Researcher in Ability-Based Tailoring of Interactive Devices at Department of Comput...
, C++, or equivalent) Experience with 3D modelling, rendering, or fabrication, and haptic feedback Familiarity with computational or optimization methods applied to interaction (e.g., computational UI
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, C++, or equivalent) Experience with 3D modelling, rendering, or fabrication, and haptic feedback Familiarity with computational or optimization methods applied to interaction (e.g., computational UI
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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this position you will conduct research within water electrolysis and membrane water treatment for electrolysis, with a particular focus on testing and modelling electrochemical cells and membranes for water
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analysis, while other competence areas include e.g. causal inference, latent variable modelling and prediction models. The section aims to maintain a strong position in these areas but also wants to expand
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machine learning to rich molecular data and uncover the molecular basis of IBD. The successful candidate will build prediction models from high-dimensional molecular measurements, with a particular focus on
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physiological and molecular responses and will feed into the project's design-test-model cycle. The position will also strengthen the unit's capacity in plant cultivation under controlled and sterile conditions
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to advance our understanding of black holes, their environments, and their extragalactic jets.The successful candidate will work with Prof. Chael’s group to advance theoretical models and simulations of black
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more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world
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on the candidate’s profile and interests, the position may also involve primary data collection, including extraction of medical chart data using natural language models and surveys of stakeholders within child and